Internet Engineering Task Force (IETF) Z. Sarker
Request for Comments: 8869 Ericsson AB
Category: Informational X. Zhu
ISSN: 2070-1721 J. Fu
Cisco Systems
January 2021
Evaluation Test Cases for Interactive Real-Time Media over Wireless
Networks
Abstract
The Real-time Transport Protocol (RTP) is a common transport choice
for interactive multimedia communication applications. The
performance of these applications typically depends on a well-
functioning congestion control algorithm. To ensure a seamless and
robust user experience, a well-designed RTP-based congestion control
algorithm should work well across all access network types. This
document describes test cases for evaluating performances of
candidate congestion control algorithms over cellular and Wi-Fi
networks.
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Engineering Task Force
(IETF). It represents the consensus of the IETF community. It has
received public review and has been approved for publication by the
Internet Engineering Steering Group (IESG). Not all documents
approved by the IESG are candidates for any level of Internet
Standard; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
https://www.rfc-editor.org/info/rfc8869.
Copyright Notice
Copyright (c) 2021 IETF Trust and the persons identified as the
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Table of Contents
1. Introduction
2. Cellular Network Specific Test Cases
2.1. Varying Network Load
2.1.1. Network Connection
2.1.2. Simulation Setup
2.1.3. Expected Behavior
2.2. Bad Radio Coverage
2.2.1. Network Connection
2.2.2. Simulation Setup
2.2.3. Expected Behavior
2.3. Desired Evaluation Metrics for Cellular Test Cases
3. Wi-Fi Networks Specific Test Cases
3.1. Bottleneck in Wired Network
3.1.1. Network Topology
3.1.2. Test/Simulation Setup
3.1.3. Typical Test Scenarios
3.1.4. Expected Behavior
3.2. Bottleneck in Wi-Fi Network
3.2.1. Network Topology
3.2.2. Test/Simulation Setup
3.2.3. Typical Test Scenarios
3.2.4. Expected Behavior
3.3. Other Potential Test Cases
3.3.1. EDCA/WMM usage
3.3.2. Effect of Heterogeneous Link Rates
4. IANA Considerations
5. Security Considerations
6. References
6.1. Normative References
6.2. Informative References
Contributors
Acknowledgments
Authors' Addresses
1. Introduction
Wireless networks (both cellular and Wi-Fi [IEEE802.11]) are an
integral and increasingly more significant part of the Internet.
Typical application scenarios for interactive multimedia
communication over wireless include video conferencing calls in a bus
or train as well as live media streaming at home. It is well known
that the characteristics and technical challenges for supporting
multimedia services over wireless are very different from those of
providing the same service over a wired network. Although the basic
test cases as defined in [RFC8867] have covered many common effects
of network impairments for evaluating RTP-based congestion control
schemes, they remain to be tested over characteristics and dynamics
unique to a given wireless environment. For example, in cellular
networks, the base station maintains individual queues per radio
bearer per user hence it leads to a different nature of interactions
between traffic flows of different users. This contrasts with a
typical wired network setting where traffic flows from all users
share the same queue at the bottleneck. Furthermore, user mobility
patterns in a cellular network differ from those in a Wi-Fi network.
Therefore, it is important to evaluate the performance of proposed
candidate RTP-based congestion control solutions over cellular mobile
networks and over Wi-Fi networks respectively.
[RFC8868] provides guidelines for evaluating candidate algorithms and
recognizes the importance of testing over wireless access networks.
However, it does not describe any specific test cases for performance
evaluation of candidate algorithms. This document describes test
cases specifically targeting cellular and Wi-Fi networks.
2. Cellular Network Specific Test Cases
A cellular environment is more complicated than its wireline
counterpart since it seeks to provide services in the context of
variable available bandwidth, location dependencies, and user
mobilities at different speeds. In a cellular network, the user may
reach the cell edge, which may lead to a significant number of
retransmissions to deliver the data from the base station to the
destination and vice versa. These radio links will often act as a
bottleneck for the rest of the network and will eventually lead to
excessive delays or packet drops. An efficient retransmission or
link adaptation mechanism can reduce the packet loss probability, but
some packet losses and delay variations will remain. Moreover, with
increased cell load or handover to a congested cell, congestion in
the transport network will become even worse. Besides, there exist
certain characteristics that distinguish the cellular network from
other wireless access networks such as Wi-Fi. In a cellular network:
* The bottleneck is often a shared link with relatively few users.
- The cost per bit over the shared link varies over time and is
different for different users.
- Leftover/unused resources can be consumed by other greedy
users.
* Queues are always per radio bearer, hence each user can have many
such queues.
* Users can experience both inter- and intra-Radio Access Technology
(RAT) handovers (see [HO-def-3GPP] for the definition of
"handover").
* Handover between cells or change of serving cells (as described in
[HO-LTE-3GPP] and [HO-UMTS-3GPP]) might cause user plane
interruptions, which can lead to bursts of packet losses, delay,
and/or jitter. The exact behavior depends on the type of radio
bearer. Typically, the default best-effort bearers do not
generate packet loss, instead, packets are queued up and
transmitted once the handover is completed.
* The network part decides how much the user can transmit.
* The cellular network has variable link capacity per user.
- It can vary as fast as a period of milliseconds.
- It depends on many factors (such as distance, speed,
interference, different flows).
- It uses complex and smart link adaptation, which makes the link
behavior ever more dynamic.
- The scheduling priority depends on the estimated throughput.
* Both Quality of Service (QoS) and non-QoS radio bearers can be
used.
Hence, a real-time communication application operating over a
cellular network needs to cope with a shared bottleneck link and
variable link capacity, events like handover, non-congestion-related
loss, and abrupt changes in bandwidth (both short term and long term)
due to handover, network load, and bad radio coverage. Even though
3GPP has defined QoS bearers [QoS-3GPP] to ensure high-quality user
experience, it is still preferable for real-time applications to
behave in an adaptive manner.
Different mobile operators deploy their own cellular networks with
their own set of network functionalities and policies. Usually, a
mobile operator network includes a range of radio access technologies
such as 3G and 4G/LTE. Looking at the specifications of such radio
technologies, it is evident that only the more recent radio
technologies can support the high bandwidth requirements from real-
time interactive video applications. Future real-time interactive
applications will impose even greater demand on cellular network
performance, which makes 4G (and beyond) radio technologies more
suitable for such genre of application.
The key factors in defining test cases for cellular networks are:
* Shared and varying link capacity
* Mobility
* Handover
However, these factors are typically highly correlated in a cellular
network. Therefore, instead of devising separate test cases for
individual important events, we have divided the test cases into two
categories. It should be noted that the goal of the following test
cases is to evaluate the performance of candidate algorithms over the
radio interface of the cellular network. Hence, it is assumed that
the radio interface is the bottleneck link between the communicating
peers and that the core network does not introduce any extra
congestion along the path. Consequently, this document has left out
of scope the combination of multiple access technologies involving
both cellular and Wi-Fi users. In this latter case, the shared
bottleneck is likely at the wired backhaul link. These test cases
further assume a typical real-time telephony scenario where one real-
time session consists of one voice stream and one video stream.
Even though it is possible to carry out tests over operational
cellular networks (e.g., LTE/5G), and actually such tests are already
available today, these tests cannot in general be carried out in a
deterministic fashion to ensure repeatability. The main reason is
that these networks are controlled by cellular operators, and there
exists various amounts of competing traffic in the same cell(s). In
practice, it is only in underground mines that one can carry out near
deterministic testing. Even there, it is not guaranteed either as
workers in the mines may carry with them their personal mobile
phones. Furthermore, the underground mining setting may not reflect
typical usage patterns in an urban setting. We, therefore, recommend
that a cellular network simulator be used for the test cases defined
in this document, for example -- the LTE simulator in [NS-3].
2.1. Varying Network Load
The goal of this test is to evaluate the performance of the candidate
congestion control algorithm under varying network load. The network
load variation is created by adding and removing network users,
a.k.a. User Equipment (UE), during the simulation. In this test
case, each user/UE in the media session is an endpoint following RTP-
based congestion control. User arrivals follow a Poisson
distribution proportional to the length of the call, to keep the
number of users per cell fairly constant during the evaluation
period. At the beginning of the simulation, there should be enough
time to warm up the network. This is to avoid running the evaluation
in an empty network where network nodes have empty buffers and low
interference at the beginning of the simulation. This network
initialization period should be excluded from the evaluation period.
Typically, the evaluation period starts 30 seconds after test
initialization.
This test case also includes user mobility and some competing
traffic. The latter includes both the same types of flows (with same
adaptation algorithms) and different types of flows (with different
services and congestion control schemes).
2.1.1. Network Connection
Each mobile user is connected to a fixed user. The connection
between the mobile user and fixed user consists of a cellular radio
access, an Evolved Packet Core (EPC), and an Internet connection.
The mobile user is connected to the EPC using cellular radio access
technology, which is further connected to the Internet. At the other
end, the fixed user is connected to the Internet via a wired
connection with sufficiently high bandwidth, for instance, 10 Gbps,
so that the system bottleneck is on the cellular radio access
interface. The wired connection in this setup does not introduce any
network impairments to the test; it only adds 10 ms of one-way
propagation delay.
The path from the fixed user to the mobile users is defined as
"downlink", and the path from the mobile users to the fixed user is
defined as "uplink". We assume that only uplink or downlink is
congested for mobile users. Hence, we recommend that the uplink and
downlink simulations are run separately.
uplink
++))) +-------------------------->
++-+ ((o))
| | / \ +-------+ +------+ +---+
+--+ / \----+ +-----+ +----+ |
/ \ +-------+ +------+ +---+
UE BS EPC Internet fixed
<--------------------------+
downlink
Figure 1: Simulation Topology
2.1.2. Simulation Setup
The values enclosed within "[ ]" for the following simulation
attributes follow the same notion as in [RFC8867]. The desired
simulation setup is as follows:
Radio environment:
Deployment and propagation model: 3GPP case 1 (see
[HO-deploy-3GPP])
Antenna: Multiple-Input and Multiple-Output (MIMO), 2D or 3D
antenna pattern
Mobility: [3 km/h, 30 km/h]
Transmission bandwidth: 10 MHz
Number of cells: multi-cell deployment (3 cells per Base Station
(BS) * 7 BS) = 21 cells
Cell radius: 166.666 meters
Scheduler: Proportional fair with no priority
Bearer: Default bearer for all traffic
Active Queue Management (AQM) settings: AQM [on, off]
End-to-end Round Trip Time (RTT): [40 ms, 150 ms]
User arrival model: Poisson arrival model
User intensity:
Downlink user intensity: {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6,
6.3, 7.0, 7.7, 8.4, 9,1, 9.8, 10.5}
Uplink user intensity: {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6,
6.3, 7.0}
Simulation duration: 91 s
Evaluation period: 30 s - 60 s
Media traffic:
Media type: Video
Media direction: [uplink, downlink]
Number of media sources per user: One (1)
Media duration per user: 30 s
Media source: same as defined in Section 4.3 of [RFC8867]
Media type: Audio
Media direction: [uplink, downlink]
Number of media sources per user: One (1)
Media duration per user: 30 s
Media codec: Constant Bit Rate (CBR)
Media bitrate: 20 Kbps
Adaptation: off
Other traffic models:
Downlink simulation: Maximum of 4 Mbps/cell (web browsing or FTP
traffic following default TCP congestion control [RFC5681])
Uplink simulation: Maximum of 2 Mbps/cell (web browsing or FTP
traffic following default TCP congestion control [RFC5681])
2.1.3. Expected Behavior
The investigated congestion control algorithms should result in
maximum possible network utilization and stability in terms of rate
variations, lowest possible end-to-end frame latency, network
latency, and Packet Loss Rate (PLR) at different cell load levels.
2.2. Bad Radio Coverage
The goal of this test is to evaluate the performance of the candidate
congestion control algorithm when users visit part of the network
with bad radio coverage. The scenario is created by using a larger
cell radius than that in the previous test case. In this test case,
each user/UE in the media session is an endpoint following RTP-based
congestion control. User arrivals follow a Poisson distribution
proportional to the length of the call, to keep the number of users
per cell fairly constant during the evaluation period. At the
beginning of the simulation, there should be enough time to warm up
the network. This is to avoid running the evaluation in an empty
network where network nodes have empty buffers and low interference
at the beginning of the simulation. This network initialization
period should be excluded from the evaluation period. Typically, the
evaluation period starts 30 seconds after test initialization.
This test case also includes user mobility and some competing
traffic. The latter includes the same kind of flows (with same
adaptation algorithms).
2.2.1. Network Connection
Same as defined in Section 2.1.1.
2.2.2. Simulation Setup
The desired simulation setup is the same as the Varying Network Load
test case defined in Section 2.1 except for the following changes:
Radio environment: Same as defined in Section 2.1.2 except for the
following:
Deployment and propagation model: 3GPP case 3 (see
[HO-deploy-3GPP])
Cell radius: 577.3333 meters
Mobility: 3 km/h
User intensity: {0.7, 1.4, 2.1, 2.8, 3.5, 4.2, 4.9, 5.6, 6.3, 7.0}
Media traffic model: Same as defined in Section 2.1.2
Other traffic models:
Downlink simulation: Maximum of 2 Mbps/cell (web browsing or FTP
traffic following default TCP congestion control [RFC5681])
Uplink simulation: Maximum of 1 Mbps/cell (web browsing or FTP
traffic following default TCP congestion control [RFC5681])
2.2.3. Expected Behavior
The investigated congestion control algorithms should result in
maximum possible network utilization and stability in terms of rate
variations, lowest possible end-to-end frame latency, network
latency, and Packet Loss Rate (PLR) at different cell load levels.
2.3. Desired Evaluation Metrics for Cellular Test Cases
The evaluation criteria document [RFC8868] defines the metrics to be
used to evaluate candidate algorithms. Considering the nature and
distinction of cellular networks, we recommend that at least the
following metrics be used to evaluate the performance of the
candidate algorithms:
* Average cell throughput (for all cells), shows cell utilization.
* Application sending and receiving bitrate, goodput.
* Packet Loss Rate (PLR).
* End-to-end media frame delay. For video, this means the delay
from capture to display.
* Transport delay.
* Algorithm stability in terms of rate variation.
3. Wi-Fi Networks Specific Test Cases
Given the prevalence of Internet access links over Wi-Fi, it is
important to evaluate candidate RTP-based congestion control
solutions over test cases that include Wi-Fi access links. Such
evaluations should highlight the inherently different characteristics
of Wi-Fi networks in contrast to their wired counterparts:
* The wireless radio channel is subject to interference from nearby
transmitters, multipath fading, and shadowing. These effects lead
to fluctuations in the link throughput and sometimes an error-
prone communication environment.
* Available network bandwidth is not only shared over the air
between concurrent users but also between uplink and downlink
traffic due to the half-duplex nature of the wireless transmission
medium.
* Packet transmissions over Wi-Fi are susceptible to contentions and
collisions over the air. Consequently, traffic load beyond a
certain utilization level over a Wi-Fi network can introduce
frequent collisions over the air and significant network overhead,
as well as packet drops due to buffer overflow at the
transmitters. This, in turn, leads to excessive delay,
retransmissions, packet losses, and lower effective bandwidth for
applications. Note further that the collision-induced delay and
loss patterns are qualitatively different from those caused by
congestion over a wired connection.
* The IEEE 802.11 standard (i.e., Wi-Fi) supports multi-rate
transmission capabilities by dynamically choosing the most
appropriate modulation and coding scheme (MCS) for the given
received signal strength. A different choice in the MCS Index
leads to different physical-layer (PHY-layer) link rates and
consequently different application-layer throughput.
* The presence of legacy devices (e.g., ones operating only in IEEE
802.11b) at a much lower PHY-layer link rate can significantly
slow down the rest of a modern Wi-Fi network. As discussed in
[Heusse2003], the main reason for such anomaly is that it takes
much longer to transmit the same packet over a slower link than
over a faster link, thereby consuming a substantial portion of air
time.
* Handover from one Wi-Fi Access Point (AP) to another may lead to
excessive packet delays and losses during the process.
* IEEE 802.11e has introduced the Enhanced Distributed Channel
Access (EDCA) mechanism to allow different traffic categories to
contend for channel access using different random back-off
parameters. This mechanism is a mandatory requirement for the Wi-
Fi Multimedia (WMM) certification in Wi-Fi Alliance. It allows
for prioritization of real-time application traffic such as voice
and video over non-urgent data transmissions (e.g., file
transfer).
In summary, the presence of Wi-Fi access links in different network
topologies can exert different impacts on the network performance in
terms of application-layer effective throughput, packet loss rate,
and packet delivery delay. These, in turn, will influence the
behavior of end-to-end real-time multimedia congestion control.
Unless otherwise mentioned, the test cases in this section choose the
PHY- and MAC-layer parameters based on the IEEE 802.11n standard.
Statistics collected from enterprise Wi-Fi networks show that the two
dominant physical modes are 802.11n and 802.11ac, accounting for 41%
and 58% of connected devices, respectively. As Wi-Fi standards
evolve over time -- for instance, with the introduction of the
emerging Wi-Fi 6 (based on IEEE 802.11ax) products -- the PHY- and
MAC-layer test case specifications need to be updated accordingly to
reflect such changes.
Typically, a Wi-Fi access network connects to a wired infrastructure.
Either the wired or the Wi-Fi segment of the network can be the
bottleneck. The following sections describe basic test cases for
both scenarios separately. The same set of performance metrics as in
[RFC8867]) should be collected for each test case.
We recommend carrying out the test cases as defined in this document
using a simulator, such as [NS-2] or [NS-3]. When feasible, it is
encouraged to perform testbed-based evaluations using Wi-Fi access
points and endpoints running up-to-date IEEE 802.11 protocols, such
as 802.11ac and the emerging Wi-Fi 6, so as to verify the viability
of the candidate schemes.
3.1. Bottleneck in Wired Network
The test scenarios below are intended to mimic the setup of video
conferencing over Wi-Fi connections from the home. Typically, the
Wi-Fi home network is not congested, and the bottleneck is present
over the wired home access link. Although it is expected that test
evaluation results from this section are similar to those in
[RFC8867], it is still worthwhile to run through these tests as
sanity checks.
3.1.1. Network Topology
Figure 2 shows the network topology of Wi-Fi test cases. The test
contains multiple mobile nodes (MNs) connected to a common Wi-Fi AP
and their corresponding wired clients on fixed nodes (FNs). Each
connection carries either an RTP-based media flow or a TCP traffic
flow. Directions of the flows can be uplink (i.e., from mobile nodes
to fixed nodes), downlink (i.e., from fixed nodes to mobile nodes),
or bidirectional. The total number of uplink/downlink/bidirectional
flows for RTP-based media traffic and TCP traffic are denoted as N
and M, respectively.
Uplink
+----------------->+
+------+ +------+
| MN_1 |)))) /=====| FN_1 |
+------+ )) // +------+
. )) // .
. )) // .
. )) // .
+------+ +----+ +-----+ +------+
| MN_N | ))))))) | | | |========| FN_N |
+------+ | | | | +------+
| AP |=========| FN0 |
+----------+ | | | | +----------+
| MN_tcp_1 | )))) | | | |======| FN_tcp_1 |
+----------+ +----+ +-----+ +----------+
. )) \\ .
. )) \\ .
. )) \\ .
+----------+ )) \\ +----------+
| MN_tcp_M |))) \=====| FN_tcp_M |
+----------+ +----------+
+<-----------------+
Downlink
Figure 2: Network Topology for Wi-Fi Test Cases
3.1.2. Test/Simulation Setup
Test duration: 120 s
Wi-Fi network characteristics:
Radio propagation model: Log-distance path loss propagation model
(see [NS3WiFi])
PHY- and MAC-layer configuration: IEEE 802.11n
MCS Index at 11: Raw data rate at 52 Mbps, 16-QAM (Quadrature
amplitude modulation) and 1/2 coding rate
Wired path characteristics:
Path capacity: 1 Mbps
One-way propagation delay: 50 ms
Maximum end-to-end jitter: 30 ms
Bottleneck queue type: Drop tail
Bottleneck queue size: 300 ms
Path loss ratio: 0%
Application characteristics:
Media traffic:
Media type: Video
Media direction: See Section 3.1.3
Number of media sources (N): See Section 3.1.3
Media timeline:
Start time: 0 s
End time: 119 s
Competing traffic:
Type of sources: Long-lived TCP or CBR over UDP
Traffic direction: See Section 3.1.3
Number of sources (M): See Section 3.1.3
Congestion control: Default TCP congestion control [RFC5681]
or CBR traffic over UDP
Traffic timeline: See Section 3.1.3
3.1.3. Typical Test Scenarios
Single uplink RTP-based media flow: N=1 with uplink direction and
M=0.
One pair of bidirectional RTP-based media flows: N=2 (i.e., one
uplink flow and one downlink flow); M=0.
One pair of bidirectional RTP-based media flows: N=2; one uplink on-
off CBR flow over UDP: M=1 (uplink). The CBR flow has ON time at
t=0s-60s and OFF time at t=60s-119s.
One pair of bidirectional RTP-based media flows: N=2; one uplink
off-on CBR flow over UDP: M=1 (uplink). The CBR flow has OFF time
at t=0s-60s and ON time at t=60s-119s.
One RTP-based media flow competing against one long-lived TCP flow
in the uplink direction: N=1 (uplink) and M=1 (uplink). The TCP
flow has start time at t=0s and end time at t=119s.
3.1.4. Expected Behavior
Single uplink RTP-based media flow: The candidate algorithm is
expected to detect the path capacity constraint, to converge to
the bottleneck link capacity, and to adapt the flow to avoid
unwanted oscillations when the sending bit rate is approaching the
bottleneck link capacity. No excessive oscillations in the media
rate should be present.
Bidirectional RTP-based media flows: The candidate algorithm is
expected to converge to the bottleneck capacity of the wired path
in both directions despite the presence of measurement noise over
the Wi-Fi connection. In the presence of background TCP or CBR
over UDP traffic, the rate of RTP-based media flows should adapt
promptly to the arrival and departure of background traffic flows.
One RTP-based media flow competing with long-lived TCP flow in the
uplink direction: The candidate algorithm is expected to avoid
congestion collapse and to stabilize at a fair share of the
bottleneck link capacity.
3.2. Bottleneck in Wi-Fi Network
The test cases in this section assume that the wired segment along
the media path is well-provisioned, whereas the bottleneck exists
over the Wi-Fi access network. This is to mimic the application
scenarios typically encountered by users in an enterprise environment
or at a coffee house.
3.2.1. Network Topology
Same as defined in Section 3.1.1.
3.2.2. Test/Simulation Setup
Test duration: 120 s
Wi-Fi network characteristics:
Radio propagation model: Log-distance path loss propagation model
(see [NS3WiFi])
PHY- and MAC-layer configuration: IEEE 802.11n
MCS Index at 11: Raw data rate at 52 Mbps, 16-QAM (Quadrature
amplitude modulation) and 1/2 coding rate
Wired path characteristics:
Path capacity: 100 Mbps
One-Way propagation delay: 50 ms
Maximum end-to-end jitter: 30 ms
Bottleneck queue type: Drop tail
Bottleneck queue size: 300 ms
Path loss ratio: 0%
Application characteristics
Media traffic:
Media type: Video
Media direction: See Section 3.2.3
Number of media sources (N): See Section 3.2.3
Media timeline:
Start time: 0 s
End time: 119 s
Competing traffic:
Type of sources: long-lived TCP or CBR over UDP
Number of sources (M): See Section 3.2.3
Traffic direction: See Section 3.2.3
Congestion control: Default TCP congestion control [RFC5681]
or CBR traffic over UDP
Traffic timeline: See Section 3.2.3
3.2.3. Typical Test Scenarios
This section describes a few test scenarios that are deemed as
important for understanding the behavior of a candidate RTP-based
congestion control scheme over a Wi-Fi network.
Multiple RTP-based media flows sharing the wireless downlink: N=16
(all downlink); M=0. This test case is for studying the impact of
contention on the multiple concurrent media flows. For an 802.11n
network, given the MCS Index of 11 and the corresponding link rate
of 52 Mbps, the total application-layer throughput (assuming
reasonable distance, low interference, and infrequent contentions
caused by competing streams) is around 20 Mbps. A total of N=16
RTP-based media flows (with a maximum rate of 1.5 Mbps each) are
expected to saturate the wireless interface in this experiment.
Evaluation of a given candidate scheme should focus on whether the
downlink media flows can stabilize at a fair share of the total
application-layer throughput.
Multiple RTP-based media flows sharing the wireless uplink: N=16
(all uplink); M=0. When multiple clients attempt to transmit
media packets uplink over the Wi-Fi network, they introduce more
frequent contentions and potential collisions. Per-flow
throughput is expected to be lower than that in the previous
downlink-only scenario. Evaluation of a given candidate scheme
should focus on whether the uplink flows can stabilize at a fair
share of the total application-layer throughput.
Multiple bidirectional RTP-based media flows: N=16 (8 uplink and 8
downlink); M=0. The goal of this test is to evaluate the
performance of the candidate scheme in terms of bandwidth fairness
between uplink and downlink flows.
Multiple bidirectional RTP-based media flows with on-off CBR
traffic over UDP: N=16 (8 uplink and 8 downlink); M=5 (uplink). The
goal of this test is to evaluate the adaptation behavior of the
candidate scheme when its available bandwidth changes due to the
departure of background traffic. The background traffic consists
of several (e.g., M=5) CBR flows transported over UDP. These
background flows are ON at time t=0-60s and OFF at time t=61-120s.
Multiple bidirectional RTP-based media flows with off-on CBR
traffic over UDP: N=16 (8 uplink and 8 downlink); M=5 (uplink). The
goal of this test is to evaluate the adaptation behavior of the
candidate scheme when its available bandwidth changes due to the
arrival of background traffic. The background traffic consists of
several (e.g., M=5) parallel CBR flows transported over UDP.
These background flows are OFF at time t=0-60s and ON at times
t=61-120s.
Multiple bidirectional RTP-based media flows in the presence of
background TCP traffic: N=16 (8 uplink and 8 downlink); M=5
(uplink). The goal of this test is to evaluate how RTP-based
media flows compete against TCP over a congested Wi-Fi network for
a given candidate scheme. TCP flows have start time at t=40s and
end time at t=80s.
Varying number of RTP-based media flows: A series of tests can be
carried out for the above test cases with different values of N,
e.g., N=[4, 8, 12, 16, 20]. The goal of this test is to evaluate
how a candidate scheme responds to varying traffic load/demand
over a congested Wi-Fi network. The start times of the media
flows are randomly distributed within a window of t=0-10s; their
end times are randomly distributed within a window of t=110-120s.
3.2.4. Expected Behavior
Multiple downlink RTP-based media flows: Each media flow is expected
to get its fair share of the total bottleneck link bandwidth.
Overall bandwidth usage should not be significantly lower than
that experienced by the same number of concurrent downlink TCP
flows. In other words, the behavior of multiple concurrent TCP
flows will be used as a performance benchmark for this test
scenario. The end-to-end delay and packet loss ratio experienced
by each flow should be within an acceptable range for real-time
multimedia applications.
Multiple uplink RTP-based media flows: Overall bandwidth usage by
all media flows should not be significantly lower than that
experienced by the same number of concurrent uplink TCP flows. In
other words, the behavior of multiple concurrent TCP flows will be
used as a performance benchmark for this test scenario.
Multiple bidirectional RTP-based media flows with dynamic
background traffic carrying CBR flows over UDP: The media flows are
expected to adapt in a timely fashion to the changes in available
bandwidth introduced by the arrival/departure of background
traffic.
Multiple bidirectional RTP-based media flows with dynamic
background traffic over TCP: During the presence of TCP background
flows, the overall bandwidth usage by all media flows should not
be significantly lower than those achieved by the same number of
bidirectional TCP flows. In other words, the behavior of multiple
concurrent TCP flows will be used as a performance benchmark for
this test scenario. All downlink media flows are expected to
obtain similar bandwidth as each other. The throughput of each
media flow is expected to decrease upon the arrival of TCP
background traffic and, conversely, increase upon their departure.
Both reactions should occur in a timely fashion, for example,
within 10s of seconds.
Varying number of bidirectional RTP-based media flows: The test
results for varying values of N -- while keeping all other
parameters constant -- is expected to show steady and stable per-
flow throughput for each value of N. The average throughput of
all media flows is expected to stay constant around the maximum
rate when N is small, then gradually decrease with increasing
value of N till it reaches the minimum allowed rate, beyond which
the offered load to the Wi-Fi network exceeds its capacity (i.e.,
with a very large value of N).
3.3. Other Potential Test Cases
3.3.1. EDCA/WMM usage
The EDCA/WMM mechanism defines prioritized QoS for four traffic
classes (or Access Categories). RTP-based real-time media flows
should achieve better performance in terms of lower delay and fewer
packet losses with EDCA/WMM enabled when competing against non-
interactive background traffic such as file transfers. When most of
the traffic over Wi-Fi is dominated by media, however, turning on WMM
may degrade performance since all media flows now attempt to access
the wireless transmission medium more aggressively, thereby causing
more frequent collisions and collision-induced losses. This is a
topic worthy of further investigation.
3.3.2. Effect of Heterogeneous Link Rates
As discussed in [Heusse2003], the presence of clients operating over
slow PHY-layer link rates (e.g., a legacy 802.11b device) connected
to a modern network may adversely impact the overall performance of
the network. Additional test cases can be devised to evaluate the
effect of clients with heterogeneous link rates on the performance of
the candidate congestion control algorithm. Such test cases, for
instance, can specify that the PHY-layer link rates for all clients
span over a wide range (e.g., 2 Mbps to 54 Mbps) for investigating
its effect on the congestion control behavior of the real-time
interactive applications.
4. IANA Considerations
This document has no IANA actions.
5. Security Considerations
The security considerations in [RFC8868] and the relevant congestion
control algorithms apply. The principles for congestion control are
described in [RFC2914], and in particular, any new method must
implement safeguards to avoid congestion collapse of the Internet.
Given the difficulty of deterministic wireless testing, it is
recommended and expected that the tests described in this document
would be done via simulations. However, in the case where these test
cases are carried out in a testbed setting, the evaluation should
take place in a controlled lab environment. In the testbed, the
applications, simulators, and network nodes ought to be well-behaved
and should not impact the desired results. It is important to take
appropriate caution to avoid leaking nonresponsive traffic with
unproven congestion avoidance behavior onto the open Internet.
6. References
6.1. Normative References
[HO-deploy-3GPP]
3GPP, "Physical layer aspects for evolved Universal
Terrestrial Radio Access (UTRA)", TS 25.814, October 2006,
<http://www.3gpp.org/ftp/specs/
archive/25_series/25.814/25814-710.zip>.
[IEEE802.11]
IEEE, "Standard for Information technology--
Telecommunications and information exchange between
systems Local and metropolitan area networks--Specific
requirements Part 11: Wireless LAN Medium Access Control
(MAC) and Physical Layer (PHY) Specifications",
IEEE 802.11-2012,
<https://ieeexplore.ieee.org/document/7786995>.
[NS3WiFi] "ns3::YansWifiChannel Class Reference",
<https://www.nsnam.org/doxygen/
classns3_1_1_yans_wifi_channel.html>.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,
<https://www.rfc-editor.org/info/rfc5681>.
[RFC8867] Sarker, Z., Singh, V., Zhu, X., and M. Ramalho, "Test
Cases for Evaluating Congestion Control for Interactive
Real-Time Media", RFC 8867, DOI 10.17487/RFC8867, January
2021, <https://www.rfc-editor.org/info/rfc8867>.
[RFC8868] Singh, V., Ott, J., and S. Holmer, "Evaluating Congestion
Control for Interactive Real-Time Media", RFC 8868,
DOI 10.17487/RFC8868, January 2021,
<https://www.rfc-editor.org/info/rfc8868>.
6.2. Informative References
[Heusse2003]
Heusse, M., Rousseau, F., Berger-Sabbatel, G., and A.
Duda, "Performance anomaly of 802.11b", IEEE INFOCOM 2003,
Twenty-second Annual Joint Conference of the IEEE Computer
and Communications Societies,
DOI 10.1109/INFCOM.2003.1208921, March 2003,
<https://ieeexplore.ieee.org/document/1208921>.
[HO-def-3GPP]
3GPP, "Vocabulary for 3GPP Specifications", 3GPP
TS 21.905, December 2009, <http://www.3gpp.org/ftp/specs/
archive/21_series/21.905/21905-940.zip>.
[HO-LTE-3GPP]
3GPP, "Evolved Universal Terrestrial Radio Access
(E-UTRA); Radio Resource Control (RRC); Protocol
specification", 3GPP TS 36.331, December 2011,
<http://www.3gpp.org/ftp/specs/
archive/36_series/36.331/36331-990.zip>.
[HO-UMTS-3GPP]
3GPP, "Radio Resource Control (RRC); Protocol
specification", 3GPP TS 25.331, December 2011,
<http://www.3gpp.org/ftp/specs/
archive/25_series/25.331/25331-990.zip>.
[NS-2] "ns-2", December 2014,
<http://nsnam.sourceforge.net/wiki/index.php/Main_Page>.
[NS-3] "ns-3 Network Simulator", <https://www.nsnam.org/>.
[QoS-3GPP] 3GPP, "Policy and charging control architecture", 3GPP
TS 23.203, June 2011, <http://www.3gpp.org/ftp/specs/
archive/23_series/23.203/23203-990.zip>.
[RFC2914] Floyd, S., "Congestion Control Principles", BCP 41,
RFC 2914, DOI 10.17487/RFC2914, September 2000,
<https://www.rfc-editor.org/info/rfc2914>.
Contributors
The following individuals contributed to the design, implementation,
and verification of the proposed test cases during earlier stages of
this work. They have helped to validate and substantially improve
this specification.
Ingemar Johansson <ingemar.s.johansson@ericsson.com> of Ericsson AB
contributed to the description and validation of cellular test cases
during the earlier stage of this document.
Wei-Tian Tan <dtan2@cisco.com> of Cisco Systems designed and set up a
Wi-Fi testbed for evaluating parallel video conferencing streams,
based upon which proposed Wi-Fi test cases are described. He also
recommended additional test cases to consider, such as the impact of
EDCA/WMM usage.
Michael A. Ramalho <mar42@cornell.edu> of AcousticComms Consulting
(previously at Cisco Systems) applied lessons from Cisco's internal
experimentation to the draft versions of the document. He also
worked on validating the proposed test cases in a virtual-machine-
based lab setting.
Acknowledgments
The authors would like to thank Tomas Frankkila, Magnus Westerlund,
Kristofer Sandlund, Sergio Mena de la Cruz, and Mirja Kühlewind for
their valuable inputs and review comments regarding this document.
Authors' Addresses
Zaheduzzaman Sarker
Ericsson AB
Torshamnsgatan 23
SE-164 83 Stockholm
Sweden
Phone: +46 10 717 37 43
Email: zaheduzzaman.sarker@ericsson.com
Xiaoqing Zhu
Cisco Systems
Building 4
12515 Research Blvd
Austin, TX 78759
United States of America
Email: xiaoqzhu@cisco.com
Jiantao Fu
Cisco Systems
771 Alder Drive
Milpitas, CA 95035
United States of America
Email: jianfu@cisco.com